The quality assessment of ultrasonic welded joints plays a critical role in ensuring the integrity and reliability of numerous industrial applications. This paper presents a comprehensive study on utilizing image processing techniques for evaluating the quality of ultrasonic welded joints. The primary objective of this research is to gain valuable insights into weld quality and defect detection using advanced image processing methods. This study employed image processing techniques to assess the quality of ultrasonic welded joints, yielding valuable insights. The edge detection technique indicated that the overall joint quality was low, while the surface detection technique identified a high defect percentage, pointing to poor welds. These findings underscore the significance of using image processing to monitor and optimize ultrasonic welding processes for enhanced accuracy and consistency. The project demonstrates the potential of image processing and machine learning in optimizing such welding procedures.